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Record W2100973690 · doi:10.1016/j.jmpt.2012.12.003

The Effects of Collateral Meridian Therapy for Knee Osteoarthritis Pain Management: A Pilot Study

2013· article· en· W2100973690 on OpenAlexaboutno aff
Huei-Chi Horng, Chang-Po Kuo, Chen‐Hwan Cherng, Chun‐Chang Yeh, Ting‐Chuan Wang, Wen‐Jinn Liaw, Shan-Chi Ko, Chih‐Shung Wong

Bibliographic record

VenueJournal of Manipulative and Physiological Therapeutics · 2013
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisVisual analogue scaleMeridian (astronomy)Physical therapyRandomized controlled trialPlaceboKnee painPain reliefSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this preliminary study was to examine whether collateral meridian (CM) therapy was feasible in treating knee osteoarthritis (OA) pain. METHODS: Twenty-eight patients with knee OA and knee pain were randomly allocated to 2 groups. The CM group patients received CM therapy, whereas the control patients received placebo treatment for knee pain relief. Patients in the CM group received 2 CM treatments weekly for 3 weeks. The outcome measures were pain intensity on a visual analog scale, and knee function was determined using the Western Ontario and McMaster Universities Osteoarthritis Index. RESULTS: In the CM group, the posttreatment visual analog scale and Western Ontario and McMaster Universities Osteoarthritis Index scores were lower than those of the control group; a significant reduction in pain intensity (P = .02, P = .01, respectively) and improvement in knee function (P = .04, P = .03, respectively) were shown in the CM group at the second and third week. CONCLUSION: Collateral meridian therapy may be feasible and effective for knee OA pain relief and knee function recovery. Therefore, additional randomized control trials are warranted.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.831
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.194
GPT teacher head0.367
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2013
Admission routes1
Has abstractyes

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